Linking Thermodynamics to Pollutant Reduction Rates by Fe(II) Bound to Iron Oxides

化学系环境化学科学项目的这一奖项支持了宾夕法尼亚州立大学克里斯托弗·戈尔斯基教授的研究。该项目的目标是改善公众获得清洁水的机会。美国的大部分饮用水来自地下蓄水层。在美国，超过126 000个地下蓄水层含有有毒化学品。这项研究旨在了解有毒化学物质如何随着时间的推移在地下水系统中转化。这项工作着眼于水的组成如何影响转化。这项工作还为6-12年级的年轻女性制定了一个新的教学计划。该教学计划旨在向年轻妇女传授地下水和化学知识。 这项工作的目的是从机理上阐明为什么污染物减少率由铁（II）结合到氧化铁矿物是高度敏感的溶液化学的变化和存在的氧化铁纳米粒子。许多类型的环境污染物在地下水中发生还原转化，并与氧化物结合的Fe（II）氧化反应相结合。这些转化会显著改变污染物的毒性、溶解度和/或生物利用度，因此在风险评估和补救工作中必须考虑到这些转化。这些反应的发生率在不同研究中差异很大。报告的反应速率常数变化超过六个数量级的共同研究的污染物。基于热力学参数的模型通常可以解释简单水化学中测得的污染物减少率之间的趋势。然而，他们未能描述收集的数据集与更复杂的水化学相关的真实的地下水系统，限制了他们的实际应用。为了解决这个问题，该项目测试了以前在文献中提出的几个工作假设，以阐明当氧化铁纳米颗粒，碳酸盐和/或天然有机物存在时污染物减少率变化的机制。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

This award from the Environmental Chemical Sciences Program in the Division of Chemistry supports research by Prof. Christopher Gorski at Pennsylvania State University. The goal of this project is to improve public access to clean water. The majority of drinking water in the U.S. comes from groundwater aquifers. In the U.S., over 126,000 groundwater aquifers contain toxic chemicals. This research aims to understand how toxic chemicals transform in groundwater systems over time. The work looks at how the composition of water affects the transformations. The work also develops a new teaching program for grade 6-12 young women. The teaching program aims to teach young women about groundwater and chemistry. This work aims to mechanistically elucidate why pollutant reduction rates by Fe(II) bound to iron oxide minerals are highly sensitive to changes in solution chemistry and the presence of iron oxide nanoparticles. Many classes of environmental pollutants undergo reductive transformations in groundwater coupled to the oxidation of oxide-bound Fe(II). These transformations significantly alter a pollutant's toxicity, solubility, and/or bioavailability, and therefore they must be taken into account in risk assessments and remediation efforts. The rates of these reactions are highly variable among studies. Reported reaction rate constants varying by over six orders of magnitude for commonly studied pollutants. Models based on thermodynamic parameters can often explain trends among measured pollutant reduction rates in simple water chemistries. However, they fail to describe datasets collected with more complex water chemistries relevant to real groundwater systems, limiting their practical use. To address this issue, this project tests several working hypotheses previously proposed in the literature to elucidate the mechanisms responsible for changes in pollutant reduction rates when iron oxide nanoparticles, carbonate, and/or natural organic matter are present.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.